This repository contains the source code and final report of Team FEB42 (Beyza Nur Kebeli and Eda Atalay) for the "제4회 K-인공지능 제조데이터 분석 경진대회" (4th K-Artificial Intelligence Manufacturing Data Analysis Competition).
The competition focused on improving productivity and enhancing the working environment in root industries (casting) companies through artificial intelligence algorithms. Participants were required to:
- Identify key challenges in die casting processes.
- Conduct data analysis and preprocessing for informed decision-making.
- Develop and compare different machine learning/deep learning models to optimize casting operations.
The final report provides detailed insights into:
- Die casting processes and their critical challenges.
- Comprehensive data analysis and preprocessing pipeline.
- Development and evaluation of various models:
- Logistic Regression
- Support Vector Machine (SVM)
- Long Short-Term Memory (LSTM)
- Feed-Forward Neural Network (FFNN)
- Performance comparison of these models.
The dataset used for this competition is available on the KAMP website under the name:
📌 "주조 공정최적화 제조AI데이터셋"
- 🔜 Source code will be uploaded soon.
- 🔜 English version of the report will be made available.